IDEAS home Printed from https://ideas.repec.org/p/ecm/ausm04/80.html
   My bibliography  Save this paper

Structurally Sound Dynamic Index Futures Hedging

Author

Listed:
  • Patrick McGlenchy
  • Paul Kofman

Abstract

Portfolio managers use index futures for a variety of reasons. Regardless of their motivation, they will keep a close eye on the relation between the futures and their stock portfolio returns. Whenever this relation is perceived to have changed, the manager will decide whether it is worthwhile to rebalance the portfolio mix. Exact measures as to when and how much rebalancing should occur, have not yet been established. This paper proposes a heuristic algorithm to dynamically update hedged portfolios. This dynamic hedging algorithm is based on a Reverse Order Cusumsquare (ROC) testing procedure, proposed by Pesaran and Timmermann (2002), to optimally determine forecast estimation windows. In a comparison with standard alternatives (expanding window, EWLS window and rolling window), we find significant improvements in hedging performance, both in- and out-of-samp

Suggested Citation

  • Patrick McGlenchy & Paul Kofman, 2004. "Structurally Sound Dynamic Index Futures Hedging," Econometric Society 2004 Australasian Meetings 80, Econometric Society.
  • Handle: RePEc:ecm:ausm04:80
    as

    Download full text from publisher

    File URL: http://repec.org/esAUSM04/up.16373.1076656779.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    2. Achim Zeileis, 2004. "Alternative boundaries for CUSUM tests," Statistical Papers, Springer, vol. 45(1), pages 123-131, January.
    3. Gita Persand & Chris Brooks & Simon P. Burke, 2003. "Multivariate GARCH models: software choice and estimation issues," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(6), pages 725-734.
    4. Lafuente, Juan A. & Novales, Alfonso, 2003. "Optimal hedging under departures from the cost-of-carry valuation: Evidence from the Spanish stock index futures market," Journal of Banking & Finance, Elsevier, vol. 27(6), pages 1053-1078, June.
    5. Cecchetti, Stephen G & Cumby, Robert E & Figlewski, Stephen, 1988. "Estimation of the Optimal Futures Hedge," The Review of Economics and Statistics, MIT Press, vol. 70(4), pages 623-630, November.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. Pesaran, M. Hashem & Timmermann, Allan, 2002. "Market timing and return prediction under model instability," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 495-510, December.
    8. Elena Andreou & Eric Ghysels, 2002. "Tests for Breaks in the Conditional Co-movements of Asset Returns," CIRANO Working Papers 2002s-59, CIRANO.
    9. Tong, Wilson H. S., 1996. "An examination of dynamic hedging," Journal of International Money and Finance, Elsevier, vol. 15(1), pages 19-35, February.
    10. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    11. Darren Butterworth & Phil Holmes, 2000. ""Ex Ante" Hedging Effectiveness of UK Stock Index Futures Contracts: Evidence for the FTSE 100 and FTSE Mid 250 Contracts," European Financial Management, European Financial Management Association, vol. 6(4), pages 441-457.
    12. Baillie, Richard T & Myers, Robert J, 1991. "Bivariate GARCH Estimation of the Optimal Commodity Futures Hedge," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(2), pages 109-124, April-Jun.
    13. Ah-Boon Sim & Ralf Zurbruegg, 2001. "Optimal hedge ratios and alternative hedging strategies in the presence of cointegrated time-varying risks," The European Journal of Finance, Taylor & Francis Journals, vol. 7(3), pages 269-283.
    14. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    reverse order cusum-square test; index futures hedging;

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ecm:ausm04:80. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum) or (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/essssea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.